Search Results - (( using case data algorithm ) OR ( data classification learning algorithm ))
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1
Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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2
A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…Annually, almost half a million women do not survive the disease and die from breast cancer. Machine learning is a subfield of artificial intelligence (AI) and computer science that uses data and algorithms to mimic how humans learn, and gradually improving its accuracy. …”
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Article -
3
An efficient and effective case classification method based on slicing
Published 2006“…The paper also discusses two of common classification algorithms that are used either in data mining or in general AI. …”
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4
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Benchmark data sets from various fields were used to test the proposed algorithms. …”
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5
Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm
Published 2020“…It focuses more on the data mining use to the Hadith dataset. We put on the Hadith dataset onto one of machine learning tools which is text classification. …”
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6
Three-term backpropagation algorithm for classification problem
Published 2006“…These datasets represents small, medium and large scale data respectively. The results obtained showed that Three-Term BP only outperforms standard BP while using small scale data but not in case of medium and large dataset. …”
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7
Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani
Published 2021“…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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Student Project -
8
Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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9
Prediction of college student academic performance using data mining techniques.
Published 2013“…This study attempts to predict the success rate of students’ academic performance by analyzing their examination results to secure a place at college level for the subsequent semester. The classification algorithms used are the Decision Tree, Naïve Bayesian, and Multilayer Perception with the highest classification accuracy by the Naive Bayes algorithm with accuracy of 95.3%. …”
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Conference or Workshop Item -
10
Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…The experiments were conducted using machine learning software Weka 3.6.9. The first experiment was to test the clean dataset with seven classification techniques. …”
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Conference or Workshop Item -
11
Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm
Published 2023“…Classification (of information); Data mining; Digital forensics; Forestry; Learning algorithms; Loudspeakers; Motion compensation; Nearest neighbor search; Speech recognition; Trees (mathematics); K-near neighbor; Logistic model tree; Logistics model; Mel frequency cepstral co-efficient; Mel frequency cepstral coefficient; Mel-frequency cepstral coefficients; Mining classification; Model trees; Nearest-neighbour; Speaker identification systems; Authentication…”
Conference Paper -
12
Cyberbullying detection: a machine learning approach
Published 2022“…Those algorithms are used in the classification or regression model to predict an input. …”
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Final Year Project / Dissertation / Thesis -
13
Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. The objective of this study is to develop an accurate and efficient model capable of recognizing the presence of children in cars based on sound data. …”
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Student Project -
14
An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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15
Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
Published 2011“…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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16
Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
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Monograph -
17
Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm
Published 2020“…MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. …”
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Article -
18
Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh.
Published 2010“…The MLP networks are trained using two types of learning algorithm, which are the Levenberg Marquardt and the Resilient Back Propagation algorithms. …”
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Research Reports -
19
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Thesis -
20
Random Undersampling on Imbalance Time Series Data for Anomaly Detection
Published 2023Conference Paper
